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@thunderpoot
thunderpoot / cc_fetch_page.py
Last active September 3, 2026 00:45
An example of fetching a page from Common Crawl using the Common Crawl Index
import requests
import json
# For parsing URLs:
from urllib.parse import quote_plus
# For parsing WARC records:
from warcio.archiveiterator import ArchiveIterator
# The URL of the Common Crawl Index server
KFZUS-F3JGV-T95Y7-BXGAS-5NHHP
T3ZWQ-P2738-3FJWS-YE7HT-6NA3K
KFZUS-F3JGV-T95Y7-BXGAS-5NHHP
65Z2L-P36BY-YWJYC-TMJZL-YDZ2S
SFZHH-2Y246-Z483L-EU92B-LNYUA
GSZVS-5W4WA-T9F2E-L3XUX-68473
FTZ8A-R3CP8-AVHYW-KKRMQ-SYDLS
Q3ZWN-QWLZG-32G22-SCJXZ-9B5S4
DAZPH-G39D3-R4QY7-9PVAY-VQ6BU
KLZ5G-X37YY-65ZYN-EUSV7-WPPBS

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@knowlet
knowlet / crossover.sh
Created March 11, 2025 06:51
Unlimited CrossOver Trial (macOS)
echo "🧹 Resetting CrossOver bottles..."
pkill CrossOver && echo "✅ CrossOver processes killed."
echo "🕒 Modifying trial timestamps..."
DATETIME=$(date -u -v -3H '+%Y-%m-%dT%TZ')
echo "✅ New trial date set to: ${DATETIME}"
defaults write com.codeweavers.CrossOver FirstRunDate -date "${DATETIME}"
defaults write com.codeweavers.CrossOver SULastCheckTime -date "${DATETIME}"
echo "✅ Updated trial timestamps in preferences."
echo "🧹 Resetting CrossOver bottles..."
find ~/Library/Application\ Support/CrossOver/Bottles/ -type f \( -name ".eval" -o -name ".update-timestamp" \) -exec rm -f "{}" +

Design Thinking

X → Graph → Effect<A, E, R>
│              │   │  │  │
│              │   │  │  └─ what each node needs     (§5)
│              │   │  └──── where the graph breaks   (§4)
│              │   └─────── what flows through nodes  (§2)
│              │
│ └─ nodes = functions, edges = data flow
@supechicken
supechicken / kernelsu.sh
Last active September 3, 2026 00:27
Build and install KernelSU kernel module/helper on Linux
# Clone repository
git clone https://github.com/supechicken/KernelSU -b waydroid-experimental --depth=1
cd KernelSU
# Build kernel module (make sure you have kernel header installed first)
cd kernel
export KVERSION="$(uname -r)"
export KBUILD_MODPOST_WARN=1
export CONFIG_KSU=m
export CONFIG_KSU_X86_PATCH_SYSCALL_DISPATCHER=y
@rjescobar
rjescobar / extend-trial-jetbrains-windows.bat
Created August 31, 2021 02:53
JetBrains IDE trial reset windows
REM Delete eval folder with licence key and options.xml which contains a reference to it
for %%I in ("WebStorm", "IntelliJ", "CLion", "Rider", "GoLand", "PhpStorm", "Resharper", "PyCharm") do (
for /d %%a in ("%USERPROFILE%\.%%I*") do (
rd /s /q "%%a/config/eval"
del /q "%%a\config\options\other.xml"
)
)
REM Delete registry key and jetbrains folder (not sure if needet but however)
rmdir /s /q "%APPDATA%\JetBrains"
@DenBread
DenBread / README.md
Created February 16, 2025 22:16
Free Activation Code for JetBrains Products

My greetings, for everyone.

How to activate any JetBrains products with 3.jetbra.in?

First we need to visit this website

https://3.jetbra.in

Click the first link with Online status, by default is ipfs.io

Screenshot 2024-12-28 at 19 22 31

@antoniopresto
antoniopresto / banco_codigo.json
Last active September 3, 2026 00:18
JSON bancos do brasil com código
[
{
"value": "001",
"label": "Banco do Brasil S.A."
},
{
"value": "003",
"label": "Banco da Amazônia S.A."
},
{
@willccbb
willccbb / grpo_demo.py
Last active September 3, 2026 00:12
GRPO Llama-1B
# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
"""
citation:
@misc{brown2025grpodemo,
title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
author={Brown, William},